VPP´s multi-level negotiation in smart grids and competitive electricity markets

The increase of distributed generation (DG) has brought about new challenges in electrical networks electricity markets and in DG units operation and management. Several approaches are being developed to manage the emerging potential of DG, such as Virtual Power Players (VPPs), which aggregate DG plants; and Smart Grids, an approach that views generation and associated loads as a subsystem. This paper presents a multi-level negotiation mechanism for Smart Grids optimal operation and negotiation in the electricity markets, considering the advantages of VPPs’ management. The proposed methodology is implemented and tested in MASCEM – a multiagent electricity market simulator, developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

Multi-agent based electricity market simulator with VPP: Conceptual and implementation issues

This paper presents a new architecture for the MASCEM, a multi-agent electricity market simulator. This is implemented in a Prolog which is integrated in the JAVA program by using the LPA Win-Prolog Intelligence Server (IS) provides a DLL interface between Win-Prolog and other applications. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets.

MASCEM - an electricity market simulator providing coalition support for virtual power players

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimization techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Players (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper details some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study based on real data.

Dgenco market balancing - cost repartition under light regulation markets

In this paper we present a new methodology, based in game theory, to obtain the market balancing between Distribution Generation Companies (DGENCO), in liberalized electricity markets. The new contribution of this methodology is the verification of the participation rate of each agent based in Nucléolo Balancing and in Shapley Value. To validate the results we use the Zaragoza Distribution Network with 42 Bus and 5 DGENCO.

ANN based day-ahead spinning reserve forecast for electricity market simulation

Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Ancillary service market simulation

Power systems operation in a liberalized environment requires that market players have access to adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper deals with ancillary services negotiation in electricity markets. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of ancillary services using two different methods (Linear Programming and Genetic Algorithm approaches) is included in the paper.

Auction of financial transmission rights in electricity market environment

An auction model is used to increase the individual profits for market players with products they do not use. A Financial Transmission Rights Auction has the goal of trade transmission rights between Bidders and helps them raise their own profits. The ISO plays a major rule on keep the system in technical limits without interfere on the auctions offers. In some auction models the ISO decide want bids are implemented on the network, always with the objective maximize the individual profits for all bidders in the auction. This paper proposes a methodology for a Financial Transmission Rights Auction and an informatics application. The application receives offers from the purchase and sale side and considers bilateral contracts as Base Case. This goal is maximize the individual profits within the system in their technical limits. The paper includes a case study for the 30 bus IEEE test case.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Cyanobacteria toxicity: potential public health impact in South Portugal populations

Cyanobacteria are prokaryotic, plantlike organisms present in lakes, recreational waters, and reservoirs, and often dominate phytoplankton communities in warm, nutrient-enriched hard waters. A stable water column rich in certain nutrients, especially nitrogen and phosphorus, is associated with favorable environmental conditions that support development of cyanobacterial population maxima or "blooms." Under specific conditions, cyanobacteria produce toxins that are responsible for acute poisoning and death of animals and humans. The main aim of this study was to correlate the presence of cyanobacteria blooms with potential toxicity to humans as a public health issue. In Portugal, seven reservoirs located in the southern region were selected and studied between 2000 and 2008. Reservoirs were characterized by physical and chemical aspects, and identification of phytoplankton communities. In the case of cyanobacterial blooms, toxins that affected the liver, nervous system, and skin were detected, namely, Microcystis aeruginosa, Aphanizomenon spp., and Oscillatoria. These findings suggest the presence of a potential risk for public health, and indicate the need to implement mitigation measures in all studied reservoirs. These measures may involve (1) water eutrophication control to avoid blooms, (2) appropriate treatment of water for human consumption, and (3) public warnings or information to those individuals that use these reservoirs for several recreational activities.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Fungal contamination in swine: a potential occupational health threat

Poor air quality in a pig-confinement building may potentially place farmers at higher health risk than other workers for exposure to airborne pollutants that may reach infectious levels. The aim of this study was to assess worker exposure to fungi in indoor environments in Portuguese swine buildings. Air samples from 7 swine farms were collected at a flow rate of 140 L/min, at 1 m height, onto malt extract agar supplemented with chloramphenicol (MEA). Surfaces samples of the same indoor sites were obtained by swabbing the surfaces. Samples from the floor covering were also collected from four of seven swine farms. All collected samples were incubated at 27°C for 5-7 days. After lab processing and incubation of obtained samples, quantitative colony-forming units (CFU)/m(3), CFU/cm(2), and CFU/g and qualitative results were determined with identification of isolated fungal species. Aspergillus versicolor was the most frequent species found in air (21%), followed by Scopulariopsis brevicaulis (17%) and Penicillium sp. (14%). Aspergillus versicolor was also the most frequent species noted on surfaces (26.6%), followed by Cladosporium sp. (22.4%) and Scopulariopsis brevicaulis (17.5%). Chrysosporium was the most frequently found genera in the new floor covering (38.5%), while Mucor was the most prevalent genera (25.1%) in used floor covering. Our findings corroborate a potential occupational health threat due to fungi exposure and suggest the need for a preventive strategy.

Riders in the storm: the professions and healthcare governance

The public sector is facing turbulent times and this also challenges the health professions who are expected to serve both the interests of the citizens and the cost-containment and austerity policies of governments. This article seeks to explore the changing role of the health professions. I introduce an approach on ‘citizen professionals’ as active players in the policy process and mediators between the state/policymakers and the citizens/patients. The aim is to highlight a transformative potential of professionalism and the connectedness with other sets of governance, like management. Empirical material from a German case study and a comparative European study serve to illustrate the arguments, drawing on policy analysis and secondary sources. The results bring the complexity of transformations and new emergent forms of professionalism into view that cannot be understood in traditional categories of conflict, exclusion and jurisdiction. Exploring the potential of the health professions to creatively respond to new challenges may reveal new opportunities for innovating healthcare policy beyond market and management.

Market impact of international sporting and cultural events

We study market reaction to the announcements of the selected country hosting the Summer and Winter Olympic Games, the World Football Cup, the European Football Cup and World and Specialized Exhibitions. We generalize previous results analyzing a large number and different types of mega-events, evaluate the effects for winning and losing countries, investigate the determinants of the observed market reaction and control for the ex ante probability of a country being a successful bidder. Average abnormal returns measured at the announcement date and around the event are not significantly different from zero. Further, we find no evidence supporting that industries, that a priori were more likely to extract direct benefits from the event, observe positive significant effects. Yet, when we control for anticipation, the stock price reactions around the announcements are significant.

New syntheses of potential biologically active xanthones and benzoxanthones

10º Encontro Nacional de Química Orgânica e 1º Simpósio Luso-Brasileiro de Química Orgânica, Lisboa, 4-6 Setembro de 2013.